De novo prediction of the genomic components and capabilities for microbial plant biomass degradation from (meta-)genomes

Aaron Weimann,Alice C Mchardy,Yulia Trukhina,Phillip B Pope,Sebastian Ga Konietzny

doi:10.1186/1754-6834-6-24

Abstract

BackgroundUnderstanding the biological mechanisms used by microorganisms for plant biomass degradation is of considerable biotechnological interest. Despite of the growing number of sequenced (meta)genomes of plant biomass-degrading microbes, there is currently no technique for the systematic determination of the genomic components of this process from these data.ResultsWe describe a computational method for the discovery of the protein domains and CAZy families involved in microbial plant biomass degradation. Our method furthermore accurately predicts the capability to degrade plant biomass for microbial species from their genome sequences. Application to a large, manually curated data set of microbial degraders and non-degraders identified gene families of enzymes known by physiological and biochemical tests to be implicated in cellulose degradation, such as GH5 and GH6. Additionally, genes of enzymes that degrade other plant polysaccharides, such as hemicellulose, pectins and oligosaccharides, were found, as well as gene families which have not previously been related to the process. For draft genomes reconstructed from a cow rumen metagenome our method predicted Bacteroidetes-affiliated species and a relative to a known plant biomass degrader to be plant biomass degraders. This was supported by the presence of genes encoding enzymatically active glycoside hydrolases in these genomes.ConclusionsOur results show the potential of the method for generating novel insights into microbial plant biomass degradation from (meta-)genome data, where there is an increasing production of genome assemblages for uncultured microbes.

Highlights

Understanding the biological mechanisms used by microorganisms for plant biomass degradation is of considerable biotechnological interest
We trained an ensemble of Support Vector Machine (SVM) classifiers to distinguish between plant biomass-degrading and non-degrading microorganisms based on either Pfam domain or CAZY gene family annotations
We used a manually curated data set of 104 microbialgenome sequence samples for this purpose, which included 19 genomes and 3 metagenomes of lignocellulose degraders and 82 genomes of non-degraders (Figure 1, Figure 2, Additional file 1: Table S1)

Summary

Introduction

Understanding the biological mechanisms used by microorganisms for plant biomass degradation is of considerable biotechnological interest. Lignocellulosic biomass is the primary component of all plants and one of the most abundant organic compounds on earth. It is a renewable, geographically distributed and a source of sugars, which can subsequently be converted into biofuels with low greenhouse gas emissions, such as ethanol. Geographically distributed and a source of sugars, which can subsequently be converted into biofuels with low greenhouse gas emissions, such as ethanol It primarily consists of cellulose, hemicellulose and lignin. Saccharification - the process of degrading lignocellulose into the individual component sugars - is of considerable biotechnological interest. The complexity of the underlying biological mechanisms and the lack of robust enzymes that can be economically produced in larger quantities currently still prevent industrial application

Methods

Results

Conclusion